Triple
T32424745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese Grand Prix |
E828547
|
entity |
| Predicate | mostFamousVenue |
P146150
|
FINISHED |
| Object | Suzuka Circuit |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Suzuka Circuit | Statement: [Japanese Grand Prix, mostFamousVenue, Suzuka Circuit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostFamousVenue Context triple: [Japanese Grand Prix, mostFamousVenue, Suzuka Circuit]
-
A.
largestVenueOf
Indicates that one venue is the largest (typically by capacity, area, or scale) among a specified set or within a particular context.
-
B.
notableVenueFor
Indicates that a venue is especially recognized or significant for hosting, presenting, or being associated with a particular entity or activity.
-
C.
significantVenueFor
Indicates that a venue plays an important or notable role in relation to a particular entity, event, or activity.
-
D.
mostFamousSetting
chosen
Indicates the location or environment most strongly and widely associated with an entity, typically recognized as its best-known or iconic setting.
-
E.
notableRecordingVenueFor
Indicates that a venue is particularly recognized or distinguished as the place where a specific recording was made.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c286ac288190843dac21651babd0 |
completed | May 3, 2026, 3:35 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:54 a.m.